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Ch 6 Introduction to Formal Statistical Inference Ch 6 Introduction to Formal Statistical Inference

Ch 6 Introduction to Formal Statistical Inference - PowerPoint Presentation

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Ch 6 Introduction to Formal Statistical Inference - PPT Presentation

61 Large Sample Confidence Intervals for a Mean A confidence interval for a parameter is a databased interval of numbers likely to include the true value of the parameter with a probabilitybased confidence ID: 578984

interval confidence true sample confidence interval sample true length large parts intervals estimate find normal standard random produced parameter

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Slide1

Ch 6 Introduction to Formal Statistical InferenceSlide2

6.1 Large Sample Confidence Intervals for a Mean

A confidence interval for a parameter is a data-based interval of numbers likely to include the true value of the parameter with a probability-based confidence.

A 95% confidence interval for µ is an interval which was constructed in a manner such that 95% of such intervals contain the true value of µ.Slide3

Interval Estimate—Confidence intervals

An interval estimate consists of an interval which will contain the quantity it is supposed to estimate with a specified probability (or degree of confidence).

Recall that for large random

samples, the

sampling distribution of the mean is approximately a normal distribution with So we will utilize some properties of normal distribution to explain a confidence interval.Slide4

For a standard normal curveSlide5

Large-sample known

s

confidence interval for

m.Slide6

Confidence Intervals

100(1-a)% CI:

80%

90%

95%

99% Slide7

Confidence Interval for Means

After computing sample mean , find a range of values such that 95% of the time the resulting range includes the true value

m

.Slide8
Slide9

X=breaking strength of a fish line.

σ

=0.10. In a random sample of size n=10,

Find a 95% confidence interval for μ, the true average breaking strength. Slide10
Slide11
Slide12
Slide13

How large a sample size is needed in order to get

an error of no

more than

0.01 with

95% probability if the sample mean is used to estimate the true mean?Solution n=385, always round up!Slide14

Example

A certain adjustment to a machine will change the length of the parts it is making but will not affect the standard deviation.

The length of the parts is normally distributed, and the standard deviation is 0.5 mm (millimeter).

After an adjustment is made, a random sample is taken to determine the mean length of parts now being produced. The observed lengths are

75.3, 76.0, 75.0, 77.0, 75.4, 76.3, 77.0, 74.9, 76.5, 75.8. Slide15

Questions

What is the parameter of interest?

Find the point estimate of the mean length of parts now being produced.

c. Find the 99% confidence interval for μ.

d. How large a sample should be taken if the population mean is to be estimated with 99% confidence to have an error not exceeding 0.2 mm ?Slide16

Solution

a.

The mean length of parts now being produced (μ);

b. x=75.92c. n=10; σ=0.5; . The 99% confidence interval is

75.512<μ<76.328

Δ

=0.20

;

since n must be an integer, n=42.